Spatial smoothing in Bayesian models: a comparison of weights matrix specifications and their impact on inference

BACKGROUND: When analysing spatial data, it is important to account for spatial autocorrelation. In Bayesian statistics, spatial autocorrelation is commonly modelled by the intrinsic conditional autoregressive prior distribution. At the heart of this model is a spatial weights matrix which controls...

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Detalles Bibliográficos
Autores principales: Duncan, Earl W., White, Nicole M., Mengersen, Kerrie
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2017
Materias:
Methodology
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5732501/
https://www.ncbi.nlm.nih.gov/pubmed/29246157
http://dx.doi.org/10.1186/s12942-017-0120-x

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5732501/
https://www.ncbi.nlm.nih.gov/pubmed/29246157
http://dx.doi.org/10.1186/s12942-017-0120-x

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